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Xuanshi Liu
Researcher at Capital Medical University
Publications - 4
Citations - 53
Xuanshi Liu is an academic researcher from Capital Medical University. The author has contributed to research in topics: Expression quantitative trait loci & Gene expression profiling. The author has an hindex of 2, co-authored 4 publications receiving 14 citations.
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Journal ArticleDOI
Blood-based multi-tissue gene expression inference with Bayesian ridge regression
TL;DR: Unlike previous methods which require genomic features or gene expression profiles of multiple tissues, this model only requires whole blood expression profile as input and helps gain insights into gene expressions of uncollected tissues from more accessible data of blood.
Journal ArticleDOI
Newborn screening with targeted sequencing: a multicenter investigation and a pilot clinical study in China.
Chanjuan Hao,Ruolan Guo,Xuyun Hu,Zhan Qi,Qi Guo,Xuanshi Liu,Yuanhu Liu,Yanhua Sun,Xiaofen Zhang,Feng Jin,Xiujie Wu,Ren Cai,Dingyuan Zeng,Xijiang Hu,Xiaohua Wang,Xiaoping Ji,Wenjie Li,Quansheng Xing,Lanfang Mu,Xiulian Jiang,Xue Yang,Weimin Yang,Zhang Yan,Qianli Yin,Ni Xin,Wei Li +25 more
TL;DR: Wang et al. as mentioned in this paper developed a panel of 465 causative genes for 596 early-onset, relatively high incidence and potentially actionable severe inherited diseases in their Newborn Screening with Targeted Sequencing (NESTS) program to screen 11,484 babies in eight Women and Children's hospitals nationwide in China retrospectively.
Journal ArticleDOI
Biological implications of genetic variations in autism spectrum disorders from genomics studies.
TL;DR: In this paper, a review of the current evidence for the known molecular genetic basis and possible pathological mechanisms as well as the risk genes and loci of ASD is presented, and functional studies for the underlying mechanisms are also implicated.
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Prioritizing long range interactions in noncoding regions using GWAS and deletions perturbed TADs
TL;DR: Zhang et al. as discussed by the authors performed a systematic inference on noncoding regions via GWAS-SNPs and deletion-perturbed TADs to boost GWAS discovery power.